Overview

Brought to you by YData

Dataset statistics

Number of variables8
Number of observations51381158
Missing cells234
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.0 GiB
Average record size in memory418.7 B

Variable types

Text5
Numeric1
Categorical2

Alerts

isOriginalTitle is highly overall correlated with typesHigh correlation
types is highly overall correlated with isOriginalTitleHigh correlation
types is highly imbalanced (74.1%) Imbalance

Reproduction

Analysis started2025-03-04 04:05:39.402271
Analysis finished2025-03-04 04:22:30.791918
Duration16 minutes and 51.39 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Distinct11456313
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size3.2 GiB
2025-03-03T23:22:49.785347image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.5436
Min length9

Characters and Unicode

Total characters490361222
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3289272 ?
Unique (%)6.4%

Sample

1st rowtt0000001
2nd rowtt0000001
3rd rowtt0000001
4th rowtt0000001
5th rowtt0000001
ValueCountFrequency (%)
tt0088814 251
 
< 0.1%
tt0168366 208
 
< 0.1%
tt0407304 203
 
< 0.1%
tt1077274 178
 
< 0.1%
tt15837206 161
 
< 0.1%
tt0099785 150
 
< 0.1%
tt2872750 150
 
< 0.1%
tt0104431 137
 
< 0.1%
tt28108011 137
 
< 0.1%
tt1067106 128
 
< 0.1%
Other values (11456303) 51379455
> 99.9%
2025-03-03T23:22:57.394288image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 102762316
21.0%
1 51204003
10.4%
2 48096575
9.8%
0 42626564
8.7%
4 38972850
 
7.9%
3 38254480
 
7.8%
8 37961325
 
7.7%
6 37364890
 
7.6%
5 31644369
 
6.5%
7 30925127
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 490361222
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 102762316
21.0%
1 51204003
10.4%
2 48096575
9.8%
0 42626564
8.7%
4 38972850
 
7.9%
3 38254480
 
7.8%
8 37961325
 
7.7%
6 37364890
 
7.6%
5 31644369
 
6.5%
7 30925127
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 490361222
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 102762316
21.0%
1 51204003
10.4%
2 48096575
9.8%
0 42626564
8.7%
4 38972850
 
7.9%
3 38254480
 
7.8%
8 37961325
 
7.7%
6 37364890
 
7.6%
5 31644369
 
6.5%
7 30925127
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 490361222
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 102762316
21.0%
1 51204003
10.4%
2 48096575
9.8%
0 42626564
8.7%
4 38972850
 
7.9%
3 38254480
 
7.8%
8 37961325
 
7.7%
6 37364890
 
7.6%
5 31644369
 
6.5%
7 30925127
 
6.3%

ordering
Real number (ℝ)

Distinct251
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2930974
Minimum1
Maximum251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size392.0 MiB
2025-03-03T23:22:57.519827image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile8
Maximum251
Range250
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0192067
Coefficient of variation (CV)0.93620207
Kurtosis82.771677
Mean4.2930974
Median Absolute Deviation (MAD)2
Skewness5.9129209
Sum2.2058432 × 108
Variance16.154022
MonotonicityNot monotonic
2025-03-03T23:22:57.666014image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 11456302
22.3%
2 8167049
15.9%
3 5424369
10.6%
4 5136636
10.0%
5 5042617
9.8%
6 4974444
9.7%
7 4933728
9.6%
8 4906124
9.5%
9 121877
 
0.2%
10 106543
 
0.2%
Other values (241) 1111469
 
2.2%
ValueCountFrequency (%)
1 11456302
22.3%
2 8167049
15.9%
3 5424369
10.6%
4 5136636
10.0%
5 5042617
9.8%
6 4974444
9.7%
7 4933728
9.6%
8 4906124
9.5%
9 121877
 
0.2%
10 106543
 
0.2%
ValueCountFrequency (%)
251 1
< 0.1%
250 1
< 0.1%
249 1
< 0.1%
248 1
< 0.1%
247 1
< 0.1%
246 1
< 0.1%
245 1
< 0.1%
244 1
< 0.1%
243 1
< 0.1%
242 1
< 0.1%

title
Text

Distinct7328099
Distinct (%)14.3%
Missing39
Missing (%)< 0.1%
Memory size4.7 GiB
2025-03-03T23:23:08.202073image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Length

Max length547520
Median length287235
Mean length17.603733
Min length1

Characters and Unicode

Total characters904499490
Distinct characters8270
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4044774 ?
Unique (%)7.9%

Sample

1st rowCarmencita
2nd rowCarmencita
3rd rowCarmencita
4th rowCarmencita - spanyol tánc
5th rowΚαρμενσίτα
ValueCountFrequency (%)
episodio 9560766
 
6.5%
episode 4839039
 
3.3%
folge 4792353
 
3.2%
épisode 4790551
 
3.2%
episódio 4784432
 
3.2%
एपिसोड 4778792
 
3.2%
エピソード 3839594
 
2.6%
de 2262495
 
1.5%
the 2164345
 
1.5%
du 981080
 
0.7%
Other values (2116258) 105084067
71.1%
2025-03-03T23:23:10.530938image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95262118
 
10.5%
o 60010712
 
6.6%
i 55726698
 
6.2%
1 49557054
 
5.5%
e 47682944
 
5.3%
d 39953560
 
4.4%
s 35923731
 
4.0%
. 32594172
 
3.6%
# 30784165
 
3.4%
a 28428019
 
3.1%
Other values (8260) 428576317
47.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 904499490
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
95262118
 
10.5%
o 60010712
 
6.6%
i 55726698
 
6.2%
1 49557054
 
5.5%
e 47682944
 
5.3%
d 39953560
 
4.4%
s 35923731
 
4.0%
. 32594172
 
3.6%
# 30784165
 
3.4%
a 28428019
 
3.1%
Other values (8260) 428576317
47.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 904499490
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
95262118
 
10.5%
o 60010712
 
6.6%
i 55726698
 
6.2%
1 49557054
 
5.5%
e 47682944
 
5.3%
d 39953560
 
4.4%
s 35923731
 
4.0%
. 32594172
 
3.6%
# 30784165
 
3.4%
a 28428019
 
3.1%
Other values (8260) 428576317
47.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 904499490
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
95262118
 
10.5%
o 60010712
 
6.6%
i 55726698
 
6.2%
1 49557054
 
5.5%
e 47682944
 
5.3%
d 39953560
 
4.4%
s 35923731
 
4.0%
. 32594172
 
3.6%
# 30784165
 
3.4%
a 28428019
 
3.1%
Other values (8260) 428576317
47.4%

region
Text

Distinct248
Distinct (%)< 0.1%
Missing195
Missing (%)< 0.1%
Memory size2.8 GiB
2025-03-03T23:23:10.816681image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.0079484
Min length2

Characters and Unicode

Total characters103170322
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row\N
2nd rowDE
3rd rowUS
4th rowHU
5th rowGR
ValueCountFrequency (%)
n 11538464
22.5%
de 5046806
9.8%
jp 5044951
9.8%
fr 5025720
9.8%
in 4979526
9.7%
es 4941086
9.6%
it 4918615
9.6%
pt 4831719
9.4%
us 1606248
 
3.1%
gb 513481
 
1.0%
Other values (238) 2934347
 
5.7%
2025-03-03T23:23:11.201268image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 16753407
16.2%
\ 11538464
11.2%
E 10268961
10.0%
I 10088253
9.8%
P 10064582
9.8%
T 9918255
9.6%
S 6777506
6.6%
R 5634492
 
5.5%
D 5168870
 
5.0%
F 5119149
 
5.0%
Other values (17) 11838383
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 103170322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 16753407
16.2%
\ 11538464
11.2%
E 10268961
10.0%
I 10088253
9.8%
P 10064582
9.8%
T 9918255
9.6%
S 6777506
6.6%
R 5634492
 
5.5%
D 5168870
 
5.0%
F 5119149
 
5.0%
Other values (17) 11838383
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 103170322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 16753407
16.2%
\ 11538464
11.2%
E 10268961
10.0%
I 10088253
9.8%
P 10064582
9.8%
T 9918255
9.6%
S 6777506
6.6%
R 5634492
 
5.5%
D 5168870
 
5.0%
F 5119149
 
5.0%
Other values (17) 11838383
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 103170322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 16753407
16.2%
\ 11538464
11.2%
E 10268961
10.0%
I 10088253
9.8%
P 10064582
9.8%
T 9918255
9.6%
S 6777506
6.6%
R 5634492
 
5.5%
D 5168870
 
5.0%
F 5119149
 
5.0%
Other values (17) 11838383
11.5%
Distinct109
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 GiB
2025-03-03T23:23:11.320940image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.0012736
Min length2

Characters and Unicode

Total characters102827757
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st row\N
2nd row\N
3rd row\N
4th row\N
5th row\N
ValueCountFrequency (%)
n 16969705
33.0%
ja 4894978
 
9.5%
fr 4835975
 
9.4%
hi 4802355
 
9.3%
es 4773886
 
9.3%
de 4766781
 
9.3%
it 4764679
 
9.3%
pt 4764501
 
9.3%
en 579041
 
1.1%
cmn 47428
 
0.1%
Other values (99) 181829
 
0.4%
2025-03-03T23:23:11.533092image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
\ 16969705
16.5%
N 16969705
16.5%
e 10138959
9.9%
t 9571965
9.3%
i 9568489
9.3%
r 4925525
 
4.8%
a 4910320
 
4.8%
j 4894980
 
4.8%
f 4840464
 
4.7%
h 4813448
 
4.7%
Other values (18) 15224197
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 102827757
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
\ 16969705
16.5%
N 16969705
16.5%
e 10138959
9.9%
t 9571965
9.3%
i 9568489
9.3%
r 4925525
 
4.8%
a 4910320
 
4.8%
j 4894980
 
4.8%
f 4840464
 
4.7%
h 4813448
 
4.7%
Other values (18) 15224197
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 102827757
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
\ 16969705
16.5%
N 16969705
16.5%
e 10138959
9.9%
t 9571965
9.3%
i 9568489
9.3%
r 4925525
 
4.8%
a 4910320
 
4.8%
j 4894980
 
4.8%
f 4840464
 
4.7%
h 4813448
 
4.7%
Other values (18) 15224197
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 102827757
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
\ 16969705
16.5%
N 16969705
16.5%
e 10138959
9.9%
t 9571965
9.3%
i 9568489
9.3%
r 4925525
 
4.8%
a 4910320
 
4.8%
j 4894980
 
4.8%
f 4840464
 
4.7%
h 4813448
 
4.7%
Other values (18) 15224197
14.8%

types
Categorical

High correlation  Imbalance 

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.9 GiB
\N
35633941 
original
11456297 
imdbDisplay
4009226 
alternative
 
136538
working
 
59529
Other values (19)
 
85627

Length

Max length20
Median length2
Mean length4.0741092
Min length2

Characters and Unicode

Total characters209332451
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st roworiginal
2nd row\N
3rd rowimdbDisplay
4th rowimdbDisplay
5th rowimdbDisplay

Common Values

ValueCountFrequency (%)
\N 35633941
69.4%
original 11456297
 
22.3%
imdbDisplay 4009226
 
7.8%
alternative 136538
 
0.3%
working 59529
 
0.1%
dvd 22310
 
< 0.1%
video 22195
 
< 0.1%
festival 21300
 
< 0.1%
tv 19378
 
< 0.1%
imdbDisplaydvd 211
 
< 0.1%
Other values (14) 233
 
< 0.1%

Length

2025-03-03T23:23:11.642541image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n 35633941
69.4%
original 11456297
 
22.3%
imdbdisplay 4009226
 
7.8%
alternative 136538
 
0.3%
working 59529
 
0.1%
dvd 22310
 
< 0.1%
video 22195
 
< 0.1%
festival 21300
 
< 0.1%
tv 19378
 
< 0.1%
imdbdisplaydvd 211
 
< 0.1%
Other values (14) 233
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
\ 35633941
17.0%
N 35633941
17.0%
i 31171589
14.9%
a 15760416
7.5%
l 15623855
7.5%
n 11652433
 
5.6%
r 11652433
 
5.6%
o 11538107
 
5.5%
g 11515872
 
5.5%
d 4076920
 
1.9%
Other values (13) 25072944
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 209332451
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
\ 35633941
17.0%
N 35633941
17.0%
i 31171589
14.9%
a 15760416
7.5%
l 15623855
7.5%
n 11652433
 
5.6%
r 11652433
 
5.6%
o 11538107
 
5.5%
g 11515872
 
5.5%
d 4076920
 
1.9%
Other values (13) 25072944
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 209332451
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
\ 35633941
17.0%
N 35633941
17.0%
i 31171589
14.9%
a 15760416
7.5%
l 15623855
7.5%
n 11652433
 
5.6%
r 11652433
 
5.6%
o 11538107
 
5.5%
g 11515872
 
5.5%
d 4076920
 
1.9%
Other values (13) 25072944
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 209332451
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
\ 35633941
17.0%
N 35633941
17.0%
i 31171589
14.9%
a 15760416
7.5%
l 15623855
7.5%
n 11652433
 
5.6%
r 11652433
 
5.6%
o 11538107
 
5.5%
g 11515872
 
5.5%
d 4076920
 
1.9%
Other values (13) 25072944
12.0%
Distinct185
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 GiB
2025-03-03T23:23:11.858848image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Length

Max length62
Median length2
Mean length2.084748
Min length2

Characters and Unicode

Total characters107116766
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)< 0.1%

Sample

1st row\N
2nd rowliteral title
3rd row\N
4th row\N
5th row\N
ValueCountFrequency (%)
n 51085404
98.7%
title 238385
 
0.5%
literal 41913
 
0.1%
alternative 39123
 
0.1%
transliterated 30559
 
0.1%
informal 28927
 
0.1%
english 28371
 
0.1%
spelling 23008
 
< 0.1%
box 21029
 
< 0.1%
new 19357
 
< 0.1%
Other values (187) 215011
 
0.4%
2025-03-03T23:23:12.193866image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
\ 51085404
47.7%
N 51085404
47.7%
t 820713
 
0.8%
e 664264
 
0.6%
l 574014
 
0.5%
i 570225
 
0.5%
389929
 
0.4%
r 297142
 
0.3%
a 281967
 
0.3%
n 252390
 
0.2%
Other values (46) 1095314
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 107116766
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
\ 51085404
47.7%
N 51085404
47.7%
t 820713
 
0.8%
e 664264
 
0.6%
l 574014
 
0.5%
i 570225
 
0.5%
389929
 
0.4%
r 297142
 
0.3%
a 281967
 
0.3%
n 252390
 
0.2%
Other values (46) 1095314
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 107116766
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
\ 51085404
47.7%
N 51085404
47.7%
t 820713
 
0.8%
e 664264
 
0.6%
l 574014
 
0.5%
i 570225
 
0.5%
389929
 
0.4%
r 297142
 
0.3%
a 281967
 
0.3%
n 252390
 
0.2%
Other values (46) 1095314
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 107116766
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
\ 51085404
47.7%
N 51085404
47.7%
t 820713
 
0.8%
e 664264
 
0.6%
l 574014
 
0.5%
i 570225
 
0.5%
389929
 
0.4%
r 297142
 
0.3%
a 281967
 
0.3%
n 252390
 
0.2%
Other values (46) 1095314
 
1.0%

isOriginalTitle
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 GiB
0
39924861 
1
11456297 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters51381158
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Length

2025-03-03T23:23:12.285018image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-03T23:23:12.379826image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Most occurring characters

ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51381158
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51381158
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51381158
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 39924861
77.7%
1 11456297
 
22.3%

Interactions

2025-03-03T23:20:04.124223image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Correlations

2025-03-03T23:23:12.451964image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
isOriginalTitleorderingtypes
isOriginalTitle1.0000.0411.000
ordering0.0411.0000.073
types1.0000.0731.000

Missing values

2025-03-03T23:20:10.543502image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-03T23:20:32.225033image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-03-03T23:21:23.702306image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

titleIdorderingtitleregionlanguagetypesattributesisOriginalTitle
0tt00000011Carmencita\N\Noriginal\N1
1tt00000012CarmencitaDE\N\Nliteral title0
2tt00000013CarmencitaUS\NimdbDisplay\N0
3tt00000014Carmencita - spanyol táncHU\NimdbDisplay\N0
4tt00000015ΚαρμενσίταGR\NimdbDisplay\N0
5tt00000016КарменситаRU\NimdbDisplay\N0
6tt00000017КарменсітаUA\NimdbDisplay\N0
7tt00000018カルメンチータJPjaimdbDisplay\N0
8tt00000021Le clown et ses chiens\N\Noriginal\N1
9tt00000022A bohóc és kutyáiHU\NimdbDisplay\N0
titleIdorderingtitleregionlanguagetypesattributesisOriginalTitle
51381148tt99168522Episódio #3.20PTpt\N\N0
51381149tt99168523एपिसोड #3.20INhi\N\N0
51381150tt99168524Épisode #3.20FRfr\N\N0
51381151tt99168525Episodio #3.20ITit\N\N0
51381152tt99168526Folge #3.20DEde\N\N0
51381153tt99168527エピソード #3.20JPja\N\N0
51381154tt99168528Episodio #3.20ESes\N\N0
51381155tt99168561The Wind\N\Noriginal\N1
51381156tt99168562The WindDE\NimdbDisplay\N0
51381157tt99168801Horrid Henry Knows It All\N\Noriginal\N1